The Genetics of Talent Development

1. The Genetics of Talent Development Putting the Gift Back into Giftedness

2. Introduction: The Nature-Nurture Controversy • Nature: • Galton’s (1869) Hereditary Genius • Galton’s (1874) English Men of Science • Nurture: • Behaviorist Learning (e.g., Watson) • Expertise Acquisition (e.g., Ericsson) • Deliberate Practice • The 10-year Rule

3. Integration: Behavioral Genetics • Environmental Effects • Shared (e.g., parental child-rearing practices) • Nonshared (e.g., birth order) • Genetic Effects • Additive versus Nonadditive (emergenic) • Static versus Dynamic (epigenetic) • Genetic  Environmental Effects • e.g., “deliberate practice”

4. Definition: Potential Talent • Any genetic trait or set of traits that • accelerates expertise acquisition and/or • enhances expert performance • in a talent domain (e.g., creativity) • Traits may be • cognitive (e.g. IQ) or dispositional (e.g., introversion), • specific (e.g., perfect pitch) or general (e.g., g)

5. Two-Part Genetic Model • Emergenic Individual Differences • Epigenetic Development

6. Emergenic Individual Differences: The Model

7. Emergenic Individual Differences: The Model • Piis the potential talent for the ith individual • Cijis the ith individual’s score on component trait j (i = 1, 2, 3, ... N) • wj is the weight given to the jth component trait (wj > 0) • Пis the multiplication operator (cf. Σ)

8. Emergenic Individual Differences: The Model

9. Emergenic Individual Differences: The Implications • the domain specificity of talent • the heterogeneity of component profiles within a talent domain

10. Hypothetical Profiles for Children with Equal High Talent (n = 5, k = 3)

11. Hypothetical Profiles for Children with Zero Talent (n = 5, k = 3)

12. Emergenic Individual Differences: The Implications • the domain specificity of talent • the heterogeneity of component profiles within a talent domain • the skewed frequency distribution of talent magnitude • the attenuated predictability of talent • the low familial inheritability of talent • the variable complexity of talent domains

13. Emergenic Individual Differences: Monte Carlo Simulation • Component scores based on 5-point (0-4) scale, randomly generated under a binomial distribution (p = .5) • N = 10,000 • Trait components’ weights set equal to unity for both models (i.e., wj = 1 for all j)

16. Epigenetic Development: The Model e.g. Cij (t) = 0, if t < sij, = aij + bijt, if sij<t < eij, and = aij + bijeij, if teij.

17. Epigenetic Development: The Model Cij (t) = aij + bijeij Cij (t) = aij + bijt Cij (t) = 0 t < sij sij<t < eij teij

18. Epigenetic Development: The Implications • the occurrence of early- and late-bloomers • the potential absence of early talent indicators • the age-dependent cross-sectional distribution of talent • the possibility of talent loss (absolute vs. relative) • the possible age-dependence of a youth’s optimal talent domain • the increased obstacles to the prediction of talent

19. Conceptual Elaboration • the ratio scaling of the talent component traits (cf. thresholds) • the postulate of uncorrelated components, and • the integration of the k component traits using a multiplicative rather than an additive function

20. Conceptual Integration • Fourfold Typology of Genetic Gifts • Additive versus Multiplicative Models • Simple versus Complex Domains

21. Fourfold Typology of Genetic Gifts

22. Caveats • Focus solely on nature • Nurture no less critical, and probably more so • Combining nature and nurture would render the phenomenon not simpler, but even more complex owing to nature-nurture interactions